Plasma miRNA Biomarkers in Limited Volume Samples for Detection of Early-stage Pancreatic Cancer.

Early detection of pancreatic ductal adenocarcinoma (PDAC) is key to improving patient outcomes; however, PDAC is usually diagnosed late. Therefore, blood-based minimally invasive biomarker assays for limited volume clinical samples are urgently needed. A novel miRNA profiling platform (Abcam Fireplex-Oncology Panel) was used to investigate the feasibility of developing early detection miRNA biomarkers with 20 µL plasma from a training set (58 stage II PDAC cases and 30 controls) and two validation sets (34 stage II PDAC cases and 25 controls; 44 stage II PDAC cases and 18 controls). miR-34a-5p [AUC = 0.77; 95% confidence interval (CI), 0.66-0.87], miR-130a-3p (AUC = 0.74; 95% CI, 0.63-0.84), and miR-222-3p (AUC = 0.70; 95% CI, 0.58-0.81) were identified as significantly differentially abundant in plasma from stage II PDAC versus controls. Although none of the miRNAs individually outperformed the currently used serologic biomarker for PDAC, carbohydrate antigen 19-9 (CA19-9), combining the miRNAs with CA 19-9 improved AUCs from 0.89 (95% CI, 0.81-0.95) for CA 19-9 alone to 0.92 (95% CI, 0.86-0.97), 0.94 (95% CI, 0.89-0.98), and 0.92 (95% CI, 0.87-0.97), respectively. Gene set enrichment analyses of transcripts correlated with high and low expression of the three miRNAs in The Cancer Genome Atlas PDAC sample set. These miRNA biomarkers, assayed in limited volume plasma together with CA19-9, discriminate stage II PDAC from controls with good sensitivity and specificity. Unbiased profiling of larger cohorts should help develop an informative early detection biomarker assay for diagnostic settings. PREVENTION RELEVANCE: Development of minimally invasive biomarker assays for detection of premalignant disease and early-stage pancreatic cancer is key to improving patient survival. This study describes a limited volume plasma miRNA biomarker assay that can detect early-stage resectable pancreatic cancer in clinical samples necessary for effective prevention and clinical intervention.

Secretory microRNAs as biomarkers of cancer.

MicroRNAs (miRNAs) are small, non-coding RNAs that regulate gene expression predominantly by inhibiting transcription and/or promoting degradation of target mRNAs also in addition to being involved in non-canonical mechanisms regulating transcription, translation and cell signaling processes. Extracellular secretory miRNAs, either in complex with specific proteins or encapsulated in microvesicles called exosomes, are transported between cells as means of intercellular communication. Secretory miRNAs in circulation remain functional after delivery to recipient cells, regulating target genes and their corresponding signaling pathways. Cancer cell secreted miRNA-mediated intercellular communication affects physiological processes associated with the disease, such as, angiogenesis, metabolic reprogramming, immune modulation, metastasis, and chemo-resistance. Given the stability of miRNAs in body fluids and their well-documented roles in deregulating cancer-relevant genetic pathways, there is considerable interest in developing secretory miRNAs as liquid biopsy biomarkers for detection, diagnosis and prognostication of cancer. In this review, we discuss salient features of miRNA biogenesis, secretion and function in cancer as well as the current state of secretory miRNA isolation and profiling methods. Furthermore, we discuss the challenges and opportunities of secretory miRNA biomarker assay development, which need to be addressed for clinical applications.

Cell-free DNA copy number variations in plasma from colorectal cancer patients.

To evaluate the clinical utility of cell-free DNA (cfDNA), we performed whole-genome sequencing to systematically examine plasma cfDNA copy number variations (CNVs) in a cohort of patients with colorectal cancer (CRC, n = 80), polyps (n = 20), and healthy controls (n = 35). We initially compared cfDNA yield in 20 paired serum-plasma samples and observed significantly higher cfDNA concentration in serum (median = 81.20 ng, range 7.18-500 ng·mL-1 ) than in plasma (median = 5.09 ng, range 3.76-62.8 ng·mL-1 ) (P < 0.0001). However, tumor-derived cfDNA content was significantly lower in serum than in matched plasma samples tested. With ~10 million reads per sample, the sequencing-based copy number analysis showed common CNVs in multiple chromosomal regions, including amplifications on 1q, 8q, and 5q and deletions on 1p, 4q, 8p, 17p, 18q, and 22q. Copy number changes were also evident in genes critical to the cell cycle, DNA repair, and WNT signaling pathways. To evaluate whether cumulative copy number changes were associated with tumor stages, we calculated plasma genomic abnormality in colon cancer (PGA-C) score by summing the most significant CNVs. The PGA-C score showed predictive performance with an area under the curve from 0.54 to 0.84 for CRC stages I-IV. Locus-specific copy number analysis identified nine genomic regions where CNVs were significantly associated with survival in stage III-IV CRC patients. A multivariate model using six of nine genomic regions demonstrated a significant association of high-risk score with shorter survival (HR = 5.33, 95% CI = 6.76-94.44, P < 0.0001). Our study demonstrates the importance of using plasma (rather than serum) to test tumor-related genomic variations. Plasma cfDNA-based tests can capture tumor-specific genetic changes and may provide a measurable classifier for assessing clinical outcomes in advanced CRC patients.

Copy number variations in urine cell free DNA as biomarkers in advanced prostate cancer.

Genetic profiling of urine cell free DNA (cfDNA) has not been evaluated in advanced prostate cancer. We performed whole genome sequencing of urine cfDNAs to identify tumor-associated copy number variations in urine before and after initiating androgen deprivation therapy in HSPC stage and docetaxel chemotherapy in CRPC stage. A log2 ratio-based copy number analysis detected common genomic abnormalities in prostate cancer including AR amplification in 5/10 CRPC patients. Other abnormalities identified included TMPRSS2-ERG fusion, PTEN gene deletion, NOTCH1 locus amplification along with genomic amplifications at 8q24.3, 9q34.3, 11p15.5 and 14q11.2, and deletions at 4q35.2, 5q31.3, 7q36.3, 12q24.33, and 16p11.2. By comparing copy number between pre- and post-treatment, we found significant copy number changes in 34 genomic loci. To estimate the somatic tumor DNA fraction in urine cfDNAs, we developed a Urine Genomic Abnormality (UGA) score algorithm that summed the top ten most significant segments with copy number changes. The UGA scores correlated with tumor burden and the change in UGA score after stage-specific therapies reflected disease progression status and overall survival. The study demonstrates the potential clinical utility of urine cfDNAs in predicting treatment response and monitoring disease progression.

Chromatin interactions and candidate genes at ten prostate cancer risk loci.

Genome-wide association studies have identified more than 100 common single nucleotide polymorphisms (SNPs) that are associated with prostate cancer risk. However, the vast majority of these SNPs lie in noncoding regions of the genome. To test whether these risk SNPs regulate their target genes through long-range chromatin interactions, we applied capture-based 3C sequencing technology to investigate possible cis-interactions at ten prostate cancer risk loci in six cell lines. We identified significant physical interactions between risk regions and their potential target genes including CAPG at 2p11.2, C2orf43 at 2p24.1, RFX6 at 6q22.1, NFASC at 1q32.1, MYC at 8q24.1 and AGAP7P at 10q11.23. Most of the interaction peaks were co-localized to regions of active histone modification and transcription factor binding sites. Expression quantitative trait locus (eQTL) analysis showed suggestive eQTL signals at rs1446669, rs699664 and rs1078004 for CAPG (p < 0.004), rs13394027 for C2orf43 (p = 2.25E-27), rs10993994 and rs4631830 for AGAP7P (p < 8.02E-5). Further analysis revealed an enhancer activity at genomic region surrounding rs4631830 which was expected to disrupt HOXB-like DNA binding affinity. This study identifies a set of candidate genes and their potential regulatory variants, and provides additional evidence showing the role of long-range chromatin interactions in prostate cancer etiology.

Plasma extracellular RNA profiles in healthy and cancer patients.

Extracellular vesicles are selectively enriched in RNA that has potential as disease biomarkers. To systemically characterize circulating extracellular RNA (exRNA) profiles, we performed RNA sequencing analysis on plasma extracellular vesicles derived from 50 healthy individuals and 142 cancer patients. Of ~12.6 million raw reads for each individual, the number of mappable reads aligned to RNA references was ~5.4 million including miRNAs (~40.4%), piwiRNAs (~40.0%), pseudo-genes (~3.7%), lncRNAs (~2.4%), tRNAs (~2.1%), and mRNAs (~2.1%). By expression stability testing, we identified a set of miRNAs showing relatively consistent expression, which may serve as reference control for exRNA quantification. By performing multivariate analysis of covariance, we identified significant associations of these exRNAs with age, sex and different types of cancers. In particular, down-regulation of miR-125a-5p and miR-1343-3p showed an association with all cancer types tested (false discovery rate <0.05). We developed multivariate statistical models to predict cancer status with an area under the curve from 0.68 to 0.92 depending cancer type and staging. This is the largest RNA-seq study to date for profiling exRNA species, which has not only provided a baseline reference profile for circulating exRNA, but also revealed a set of RNA candidates for reference controls and disease biomarkers.

Genomic variations in plasma cell free DNA differentiate early stage lung cancers from normal controls.

OBJECTIVES: Cell free tumor DNA (cfDNA) circulating in blood has a great potential as biomarker for cancer clinical management. The objective of this study is to evaluate if cfDNA in blood plasma is detectable in early stage lung cancer patients. MATERIALS AND METHODS: We extracted cfDNAs and tumor tissue DNAs from 8 lung adenocarcinoma patients. We also extracted cfDNAs from 8 normal controls. To evaluate copy number variations (CNV) and identify potential mutations, we performed low pass whole genome sequencing and targeted sequencing of 50 cancer genes. To accurately reflect the tumor-associated genomic abnormality burden in plasma, we developed a new scoring algorithm, plasma genomic abnormality (PGA) score, by summarizing absolute log2 ratios in most variable genomic regions. We performed digital PCR and allele-specific PCR to validate mutations detected by targeted sequencing. RESULTS AND CONCLUSIONS: The median yield of cfDNA in 400 ul plasma was 4.9 ng (range 2.25-26.98 ng) in patients and 2.32 ng (range 1.30-2.81 ng) in controls (p=0.003). The whole genome sequencing generated approximately 20 million mappable sequence reads per subject and 5303 read counts per 1Mb genomic region. Log2 ratio-based CNV analysis showed significant chromosomal abnormality in cancer tissue DNAs and subtle but detectable differences in cfDNAs between patients and controls. Genomic abnormality analysis showed that median PGA score was 9.28 (7.38-11.08) in the 8 controls and 19.50 (5.89-64.47) in the 8 patients (p=0.01). Targeted deep sequencing in tumor tissues derived from the 8 patients identified 14 mutations in 12 different genes. The PCR-based assay confirmed 3 of 6 selected mutations in cfDNAs. These results demonstrated that the PGA score and cfDNA mutational analysis could be useful tool for the early detection of lung cancer. These blood-based genomic and genetic assays are noninvasive and may sensitively distinguish early stage disease when combined with other existing screening strategies including low-dose CT scanning.

Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer.

Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locus-specific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer.

Exosomal miR-1290 and miR-375 as prognostic markers in castration-resistant prostate cancer.

BACKGROUND: Extracellular microRNAs (miRNAs) embedded in circulating exosomes may serves as prognostic biomarkers in cancer. OBJECTIVE: To identify and evaluate plasma exosomal miRNAs for prognosis in castration-resistant prostate cancer (CRPC). DESIGN, SETTING, AND PARTICIPANTS: RNA sequencing was performed to identify candidate exosomal miRNAs associated with overall survival in a screening cohort of 23 CRPC patients. Candidate miRNAs were further evaluated for prognosis using quantitative real-time polymerase chain reaction in a follow-up cohort of 100 CRPC patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Cox regression and Kaplan-Meier survival analyses were used to evaluate survival association using candidate miRNAs along with clinical prognostic factors. RESULTS AND LIMITATIONS: RNA sequencing in screening cohort generated approximately 6.80 million mappable reads per patient. Of those with normalized read counts ≥ 5, 43% were mapped to miRNAs for a total of 375 known and 57 novel miRNAs. Cox regression analysis identified an association of miR-1290, -1246, and -375 with overall survival (false discover rate < 0.05). Of those, higher levels of miR-1290 and -375 were significantly associated with poor overall survival (p < 0.004) in the follow-up cohort. Incorporation of miR-1290/-375 into putative clinical prognostic factors-based models in CRPC stage significantly improved predictive performance with a time-dependent area under the curve increase from 0.66 to 0.73 (p = 6.57 × 10(-6)). CONCLUSIONS: Plasma exosomal miR-1290 and miR-375 are promising prognostic biomarkers for CRPC patients. Prospective validation is needed for further evaluation of these candidate miRNAs. PATIENT SUMMARY: In this study, we evaluated whether small RNAs circulating in blood could be used to predict clinical outcomes in late-stage prostate cancer patients. We identified two blood-based small RNAs whose levels showed significant association with survival. Our results warrant further investigation because the noninvasive blood-based test has great potential in the management of late-stage prostate cancer.

Prostate cancer risk locus at 8q24 as a regulatory hub by physical interactions with multiple genomic loci across the genome.

Chromosome 8q24 locus contains regulatory variants that modulate genetic risk to various cancers including prostate cancer (PC). However, the biological mechanism underlying this regulation is not well understood. Here, we developed a chromosome conformation capture (3C)-based multi-target sequencing technology and systematically examined three PC risk regions at the 8q24 locus and their potential regulatory targets across human genome in six cell lines. We observed frequent physical contacts of this risk locus with multiple genomic regions, in particular, inter-chromosomal interaction with CD96 at 3q13 and intra-chromosomal interaction with MYC at 8q24. We identified at least five interaction hot spots within the predicted functional regulatory elements at the 8q24 risk locus. We also found intra-chromosomal interaction genes PVT1, FAM84B and GSDMC and inter-chromosomal interaction gene CXorf36 in most of the six cell lines. Other gene regions appeared to be cell line-specific, such as RRP12 in LNCaP, USP14 in DU-145 and SMIN3 in lymphoblastoid cell line. We further found that the 8q24 functional domains more likely interacted with genomic regions containing genes enriched in critical pathways such as Wnt signaling and promoter motifs such as E2F1 and TCF3. This result suggests that the risk locus may function as a regulatory hub by physical interactions with multiple genes important for prostate carcinogenesis. Further understanding genetic effect and biological mechanism of these chromatin interactions will shed light on the newly discovered regulatory role of the risk locus in PC etiology and progression.

eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing.

BACKGROUND: RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. RESULTS: We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification" includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module "mRNA identification" includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module "Target screening" provides expression profiling analyses and graphic visualization. The module "Self-testing" offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program's functionality. CONCLUSIONS: eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory.

Extracellular microRNAs in urologic malignancies: chances and challenges.

Small noncoding RNAs that are 19-23 nucleotides long, known as microRNAs (miRNAs), are involved in almost all biological mechanisms during carcinogenesis. Recent studies show that miRNAs released from live cells are detectable in body fluids and may be taken up by other cells to confer cell-cell communication. These released miRNAs (here referred to as extracellular miRNAs) are often protected by RNA-binding proteins or embedded inside circulating microvesicles. Due to their relative stability, extracellular miRNAs are believed to be promising candidates as biomarkers for diagnosis and prognosis of disease, or even as therapeutic agents for targeted treatment. In this review, we first describe biogenesis and characteristics of these miRNAs. We then summarize recent publications involving extracellular miRNA profiling studies in three representative urologic cancers, including: prostate cancer, bladder cancer, and renal cell carcinoma. We focus on the diagnostic, prognostic, and therapeutic potential of these miRNAs in biological fluids, such as serum, plasma, and urine. Finally, we discuss advantages and challenges of these miRNAs in clinical applications.

Characterization of human plasma-derived exosomal RNAs by deep sequencing.

BACKGROUND: Exosomes, endosome-derived membrane microvesicles, contain specific RNA transcripts that are thought to be involved in cell-cell communication. These RNA transcripts have great potential as disease biomarkers. To characterize exosomal RNA profiles systemically, we performed RNA sequencing analysis using three human plasma samples and evaluated the efficacies of small RNA library preparation protocols from three manufacturers. In all we evaluated 14 libraries (7 replicates). RESULTS: From the 14 size-selected sequencing libraries, we obtained a total of 101.8 million raw single-end reads, an average of about 7.27 million reads per library. Sequence analysis showed that there was a diverse collection of the exosomal RNA species among which microRNAs (miRNAs) were the most abundant, making up over 42.32% of all raw reads and 76.20% of all mappable reads. At the current read depth, 593 miRNAs were detectable. The five most common miRNAs (miR-99a-5p, miR-128, miR-124-3p, miR-22-3p, and miR-99b-5p) collectively accounted for 48.99% of all mappable miRNA sequences. MiRNA target gene enrichment analysis suggested that the highly abundant miRNAs may play an important role in biological functions such as protein phosphorylation, RNA splicing, chromosomal abnormality, and angiogenesis. From the unknown RNA sequences, we predicted 185 potential miRNA candidates. Furthermore, we detected significant fractions of other RNA species including ribosomal RNA (9.16% of all mappable counts), long non-coding RNA (3.36%), piwi-interacting RNA (1.31%), transfer RNA (1.24%), small nuclear RNA (0.18%), and small nucleolar RNA (0.01%); fragments of coding sequence (1.36%), 5' untranslated region (0.21%), and 3' untranslated region (0.54%) were also present. In addition to the RNA composition of the libraries, we found that the three tested commercial kits generated a sufficient number of DNA fragments for sequencing but each had significant bias toward capturing specific RNAs. CONCLUSIONS: This study demonstrated that a wide variety of RNA species are embedded in the circulating vesicles. To our knowledge, this is the first report that applied deep sequencing to discover and characterize profiles of plasma-derived exosomal RNAs. Further characterization of these extracellular RNAs in diverse human populations will provide reference profiles and open new doors for the development of blood-based biomarkers for human diseases.